Data Engineer

Key Responsibilities

• Design, build, and maintain scalable, secure, and cost-efficient data solutions on a cloud data platform (Microsoft Azure/Microsoft Fabric preferred; AWS and comparable platforms considered).
• Develop and optimize modern ETL/ELT pipelines supporting enterprise systems such as Salesforce, MRI, and other internal and external data sources.
• Lead cloud data platform modernization and migration initiatives, reducing manual processes and improving data reliability.
• Define and enforce data architecture, governance, security, and quality standards across the data ecosystem.
• Partner closely with BI and analytics teams to enable trusted reporting and insights (e.g., Power BI and semantic models) across the organization.
• Ensure high performance, availability, and cost efficiency through monitoring, performance tuning, and continuous optimization.
• Translate complex business requirements into scalable, future-proof data architectures in collaboration with business and engineering stakeholders.
• Support the development of training materials and conduct workshops for team members.
• Evaluate and adopt new data technologies and capabilities (e.g., Microsoft Fabric, Azure services, Snowflake, Databricks) to drive innovation and long-term platform scalability.
• Contribute to the company’s purpose by improving the data platform and analytics capabilities that enable better decision-making and positive impact.
• Travel up to 15%.

Qualifications

• Required: Bachelor’s degree in computer science, Engineering, Information Systems, or equivalent practical experience. 5+ years of experience in data engineering, with at least 3+ years designing and delivering cloud-based data solutions (Azure preferred; AWS and other major cloud platforms considered).
• Hands-on experience with modern cloud data engineering tools and services, such as Microsoft Fabric (Data Factory, Synapse), Azure Data Factory/Azure Synapse, Databricks, and/or Snowflake.
• Proven expertise in building and optimizing large-scale ETL/ELT pipelines for high-volume, enterprise data environments.
• Advanced SQL skills and experience with data modeling for analytics and reporting workloads.
• Solid understanding of data governance, security, data quality, and access control within cloud data platforms (Azure preferred).
• Demonstrated ability to translate complex business requirements into scalable, production-grade data architectures.
• Strong communication skills with the ability to collaborate effectively across business, analytics, and engineering teams.
• PREFERRED: Cloud and data platform certifications (Azure preferred), such as DP-203 (Data Engineering on Microsoft Azure) or DP-600 (Microsoft certified: Fabric Analytics Engineer Associate) or equivalent AWS certifications, or Snowflake/Databricks credentials.
• Experience with Power BI and enabling self-service analytics through a governed semantic layer (Microsoft Fabric experience a plus).
• Familiarity with cloud cost optimization, performance tuning, and monitoring of data platforms at scale.
• Experience with cloud data platform migrations and modernization initiatives.
• Knowledge of CI/CD, infrastructure-as-code, and automated deployment patterns for data solutions.
• Experience working in large-scale, enterprise or real estate / financial services data environments.

Pay

The expected salary range for this position is between $115,000 and $140,000. The actual compensation will be based on factors such as scope and responsibilities of the position, candidate's work experience, education/training, job-related skills, internal peer equity, market and business considerations and other factors permitted by law.